Magalhaes R.P.,Federal University of Ceará |
Monteiro J.M.,Federal University of Ceará |
Vidal V.M.P.,Federal University of Ceará |
De Macedo J.A.F.,Federal University of Ceará |
And 3 more authors.
ICEIS 2013 - Proceedings of the 15th International Conference on Enterprise Information Systems | Year: 2013
Linked data applications express integrated views using the SPARQL query language. A SPARQL federated query is submitted to a query engine that processes it over the distributed SPARQL endpoints. However, achieving an efficient execution of such a SPARQL federated query is hard. This is mainly due to the fact that query processors have little or no statistical information about the data stored at the endpoints. Moreover, the endpoints, usually, are autonomous and unstable. This paper presents QEF-LD, a query engine that enables the efficient execution of federated queries over multiple Linked Data sources. Experiments demonstrate the feasibility of QEF-LD when compared to available federated query engines.
Zorrilla R.,Extreme Data Laboratory |
Poltosi M.,Extreme Data Laboratory |
Gadelha L.,Extreme Data Laboratory |
Porto F.,Extreme Data Laboratory |
And 6 more authors.
Data Science Journal | Year: 2014
Data generated by environmental research in Antarctica are essential in evaluating how its biodiversity and environment are affected by global-scale changes triggered by ever-increasing human activities. In this work, we describe BrAntIS, the Brazilian Information System on Antarctic Environmental Research, which enables the acquiring, storing, and querying of research data generated by the Brazilian National Institute for Science and Technology on Antarctic Environmental Research. BrAntIS' data model reflects data acquisition and analysis conducted by scientists and organized around field expeditions. We describe future functionalities, such as the use of linked data techniques and support for scientific workflows.